Paper Info
Title
Quantifying the performance and energy efficiency of advanced cache indexing for GPGPU computing.
Abstract
To achieve higher performance and energy efficiency, GPGPU architectures have recently begun to employ hardware caches. Adding caches to GPGPUs, however, does not always guarantee improved performance and energy efficiency due to the thrashing in small caches shared by thousands of threads. While prior work has proposed warp-scheduling and cache-bypassing techniques to address this issue, relatively little work has been done in the context of advanced cache indexing (ACI).To bridge this gap, this work investigates the effectiveness of ACI for high-performance and energy-efficient GPGPU computing. We discuss the design and implementation of static and adaptive cache indexing schemes for GPGPUs. We then quantify the effectiveness of the ACI schemes based on a cycle-accurate GPGPU simulator. Our quantitative evaluation demonstrates that the ACI schemes are effective in that they provide significant performance and energy-efficiency gains over the conventional indexing scheme. Further, we investigate the performance sensitivity of ACI to key architectural parameters (e.g., indexing latency and cache associativity). Our experimental results show that the ACI schemes are promising in that they continue to provide significant performance gains even when additional indexing latency occurs due to the hardware complexity and the baseline cache is enhanced with high associativity or large capacity.
Year
DOI
Venue
2016
10.1016/j.micpro.2016.01.003
Microprocessors and Microsystems - Embedded Hardware Design
Keywords
Field
DocType
Advanced cache indexing,GPGPU computing,High performance,Energy efficiency
Search engine,Computer science,Latency (engineering),Efficient energy use,Cache,Parallel computing,Search engine indexing,Real-time computing,Thread (computing),Thrashing,General-purpose computing on graphics processing units
Journal
Volume
Issue
ISSN
43
C
0141-9331
Citations 
PageRank 
References 
6
0.47
22
Authors
2
Name
Order
Citations
PageRank
kyu yeun kim1102.22
Woongki Baek240225.85